OBJECTIVES: To analyze the molecular mechanism of Xixian Pills for treatment of rheumatoid arthritis (RA). METHODS: Forty-eight rats were randomized into 6 groups (n=8), including a normal control group, a collagen-induced arthritis (CIA) model group, 3 Xixian Pills treatment (200, 400 and 800 mg/kg) groups, and a Tripterygium glycosides tablet (TGT) treatment group. In the latter 4 groups, the rats were treated with daily gavage of Xixian Pills or TGT 2 weeks after CIA modeling for 3 consecutive weeks. The differentially expressed proteins in high-dose Xixian Pills group and the model group compared with the normal control group were screened based on the tandem mass spectrometry tag (TMT) technology, and the core targets and signaling pathways were analyzed. The immune cell infiltration and gene expression data were analyzed using ggplot2 and tidyverse packages, and the correlation coefficients between the core targets and the immune cells were calculated. RESULTS: The CIA rats showed significantly increased serum levels of TNF-α and IL-6 and lowered serum IL-10 level. Treatments with high- and medium-dose Xixian Pills and TGT all significantly reduced serum TNF‑α and IL-6 and increased IL-10 levels in CIA rats. Proteomic analysis identified 160 differential proteins between the model group and high-dose Xixian Pills group, and the core targets included CCL5, STAT1, GZMB and IL7R. The areas under the ROC curve of CCL5 and STAT1 were both greater than 0.9. Immunohistochemical and immunofluorescence staining revealed increased levels of CCL5 and STAT1 in the ankle joints of CIA rats, which were significantly decreased after treatment with Xixian Pills. CONCLUSIONS Treatment with Xixian Pills offers protection of the joints in CIA rats possibly by inhibiting joint inflammation via regulating protein expressions of CCL5 and STAT1.
Animals ; Drugs, Chinese Herbal/pharmacology* ; Rats ; Arthritis, Rheumatoid/metabolism* ; Proteomics ; Tripterygium/chemistry* ; Arthritis, Experimental/metabolism* ; Tumor Necrosis Factor-alpha/blood* ; Interleukin-10/blood* ; Interleukin-6/blood* ; Male ; Rats, Sprague-Dawley ; Signal Transduction

Oral squamous cell carcinoma (OSCC) is the most common manifestation of oral cancer. It has been proposed that periodontal pathogens contribute to OSCC progression, mainly by their virulence factors. However, the main periodontal pathogen and its mechanism to modulate OSCC cells remains not fully understood. In this study we investigate the main host-pathogen pathways in OSCC by computational proteomics and the mechanism behind cancer progression by the oral microbiome. The main host-pathogen pathways were analyzed in the secretome of biopsies from patients with OSCC and healthy controls by mass spectrometry. Then, functional assays were performed to evaluate the host-pathogen pathways highlighted in oral cancer. Host proteins associated with LPS response, cell migration/adhesion, and metabolism of amino acids were significantly upregulated in the human cancer proteome, whereas the complement cascade was downregulated in malignant samples. Then, the microbiome analysis revealed large number and variety of peptides from Fusobacterium nucleatum (F. nucleatum) in OSCC samples, from which several enzymes from the L-glutamate degradation pathway were found, indicating that L-glutamate from cancer cells is used as an energy source, and catabolized into butyrate by the bacteria. In fact, we observed that F. nucleatum modulates the cystine/glutamate antiporter in an OSCC cell line by increasing SLC7A11 expression, promoting L-glutamate efflux and favoring bacterial infection. Finally, our results showed that F. nucleatum and its metabolic derivates promote tumor spheroids growth, spheroids-derived cell detachment, epithelial-mesenchymal transition and Galectin-9 upregulation. Altogether, F. nucleatum promotes pro-tumoral mechanism in oral cancer.
Humans ; Fusobacterium nucleatum/metabolism* ; Mouth Neoplasms/metabolism* ; Disease Progression ; Proteomics ; Carcinoma, Squamous Cell/metabolism* ; Host-Pathogen Interactions ; Metabolic Networks and Pathways ; Case-Control Studies ; Mass Spectrometry

Stem cells play a crucial role in maintaining tissue regenerative capacity and homeostasis. However, mechanisms associated with stem cell senescence require further investigation. In this study, we conducted a proteomic analysis of human dental pulp stem cells (HDPSCs) obtained from individuals of various ages. Our findings showed that the expression of NUP62 was decreased in aged HDPSCs. We discovered that NUP62 alleviated senescence-associated phenotypes and enhanced differentiation potential both in vitro and in vivo. Conversely, the knocking down of NUP62 expression aggravated the senescence-associated phenotypes and impaired the proliferation and migration capacity of HDPSCs. Through RNA-sequence and decoding the epigenomic landscapes remodeled induced by NUP62 overexpression, we found that NUP62 helps alleviate senescence in HDPSCs by enhancing the nuclear transport of the transcription factor E2F1. This, in turn, stimulates the transcription of the epigenetic enzyme NSD2. Finally, the overexpression of NUP62 influences the H3K36me2 and H3K36me3 modifications of anti-aging genes (HMGA1, HMGA2, and SIRT6). Our results demonstrated that NUP62 regulates the fate of HDPSCs via NSD2-dependent epigenetic reprogramming.
Humans ; Dental Pulp/cytology* ; Nuclear Pore Complex Proteins/genetics* ; Cellular Senescence/genetics* ; Stem Cells/metabolism* ; Epigenesis, Genetic ; Cell Proliferation ; Cell Differentiation ; Histone-Lysine N-Methyltransferase/metabolism* ; Cells, Cultured ; Cellular Reprogramming ; Cell Movement ; Proteomics

Acute respiratory distress syndrome (ARDS) is a clinical syndrome characterized by diffuse alveolar and interstitial edema caused by damage to alveolar-capillary and epithelial cells, often induced by infection, sepsis, trauma, and other factors. It is marked by progressive hypoxemia and respiratory distress. Due to the diverse causes of ARDS, the unclear pathogenesis, and the absence of effective predictive markers or biomarkers, there are no effective treatment measures available, resulting in a high mortality rate. ARDS is increasingly recognized for its heterogeneity, biomarkers, and the emergence of new opportunities for the development of diagnostic tools and personalized treatment strategies provided by omics technologies. A single omics analysis cannot fully reveal the heterogeneity and complexity of ARDS, while multi-omics analysis can provide a more systematic and comprehensive understanding of ARDS. Using clinical samples is closer to the actual disease situation compared to animal models. Multi-omics studies based on clinical samples have achieved significant progress in elucidating the pathophysiology of ARDS, identifying ARDS subtypes, and identifying biomarkers related to ARDS. This review focuses on the current applications of genomics, transcriptomics, metabolomics, and proteomics analyses based on clinical samples in the ARDS field, with a focus on the application of these omics methods in ARDS heterogeneity, potential biomarkers, and pathogenesis. It also introduces the differences in the application of different clinical samples in ARDS omics research, in order to gain a deeper and more comprehensive understanding of the pathogenesis of ARDS and explore new strategies for its prevention and treatment.
Respiratory Distress Syndrome/diagnosis* ; Humans ; Metabolomics ; Proteomics ; Genomics ; Biomarkers ; Multiomics

OBJECTIVE: To identify and validate novel biomarkers for the early diagnosis of sepsis-associated acute kidney injury (SA-AKI) and precise continuous renal replacement therapy (CRRT) using proteomics. METHODS: A prospective multicenter cohort study was conducted. Patients with sepsis admitted to five hospitals in Taizhou City of Zhejiang Province from April 2019 to December 2021 were continuously enrolled, based on the occurrence of acute kidney injury (AKI). Sepsis patients were divided into SA-AKI group and non-SA-AKI group, and healthy individuals who underwent physical examinations during the same period were used as control (NC group). Peripheral blood samples from participants were collected for protein mass spectrometry analysis. Differentially expressed proteins were identified, and functional enrichment analysis was conducted on these proteins. The levels of target proteins were detected by enzyme linked immunosorbent assay (ELISA), and the predictive value of target protein for SA-AKI were evaluated by receiver operator characteristic curve (ROC curve). Additionally, sepsis patients and healthy individuals were selected from one hospital to externally verify the expression level of the target protein and its predictive value for SA-AKI, as well as the accuracy of CRRT treatment. RESULTS: A total of 37 patients with sepsis (including 19 with AKI and 18 without AKI) and 31 healthy individuals were enrolled for proteomic analysis. Seven proteins were identified with significantly differential expression between the SA-AKI group and non-SA-AKI group: namely cystatin C (CST3), β ₂-microglobulin (β ₂M), insulin-like growth factor-binding protein 4 (IGFBP4), complement factor I (CFI), complement factor D (CFD), CD59, and glycoprotein prostaglandin D2 synthase (PTGDS). Functional enrichment analysis revealed that these proteins were involved in immune response, complement activation, coagulation cascade, and neutrophil degranulation. ELISA results demonstrated specific expression of each target protein in the SA-AKI group. Additionally, 65 patients with sepsis (38 with AKI and 27 without AKI) and 20 healthy individuals were selected for external validation of the 7 target proteins. ELISA results showed that there were statistically significant differences in the expression levels of CST3, β ₂M, IGFBP4, CFD, and CD59 between the SA-AKI group and non-SA-AKI group. ROC curve analysis indicated that the area under the curve (AUC) values of CST3, β ₂M, IGFBP4, CFD, and CD59 for predicting SA-AKI were 0.788, 0.723, 0.723, 0.795, and 0.836, respectively, all exceeding 0.7. Further analysis of patients who underwent CRRT or not revealed that IGFBP4 had a good predictive value, with an AUC of 0.84. CONCLUSIONS Based on proteomic analysis, CST3, β ₂M, IGFBP4, CFD, and CD59 may serve as potential biomarkers for the diagnosis of SA-AKI, among which IGFBP4 might be a potential biomarker for predicting the need for CRRT in SA-AKI patients. However, further clinical validation is required.
Humans ; Sepsis/complications* ; Acute Kidney Injury/blood* ; Proteomics ; Prospective Studies ; Biomarkers/blood* ; Male ; Female ; beta 2-Microglobulin/blood* ; Middle Aged ; Cystatin C/blood* ; Aged

Xiaoaiping (XAP) Injection demonstrates the anti-prostate cancer (PCa) effects, yet the underlying mechanism remains unclear. This study aims to investigate the impact of XAP on PCa and elucidate its mechanism of action. PCa cell proliferation was evaluated using a cell counting kit-8 (CCK-8) assay. Cell apoptosis was assessed through Hoechst staining and Western blotting assays. Proteomics technology was employed to identify key molecules and significant signaling pathways modulated by XAP in PCa cells. To further validate potential key genes and important pathways, a series of assays were conducted, including acridine orange (AO) staining, transmission electron microscopy, and immunofluorescence assays. The molecular mechanism of XAP against PCa in vivo was examined using a PC3 xenograft mouse model. Results demonstrated that XAP significantly inhibited cell proliferation in multiple PCa cell lines. In C4-2 and prostate cancer cell line-3 (PC3) cells, XAP induced cellular apoptosis, evidenced by reduced B-cell lymphoma 2 (Bcl-2) levels and elevated Bcl-2-associated X (Bax) levels. Proteomic, immunofluorescence, and quantitative reverse transcription-polymerase chain reaction (qRT-PCR) investigations revealed a strong correlation between forkhead box O3a (FoxO3a) autophagic degradation and the anti-PCa action of XAP. XAP hindered autophagy by reducing the expression levels of autophagy-related protein 5 (Atg5)/autophagy-related protein 12 (Atg12) and enhancing FoxO3a expression and nuclear translocation. Furthermore, XAP exhibited potent anti-PCa action in PC3 xenograft mice and triggered FoxO3a nuclear translocation in tumor tissue. These findings suggest that XAP induces PCa apoptosis via inhibition of FoxO3a autophagic degradation, potentially offering a novel perspective on XAP injection as an effective anticancer therapy for PCa.
Male ; Humans ; Prostatic Neoplasms/physiopathology* ; Autophagy/drug effects* ; Animals ; Drugs, Chinese Herbal/pharmacology* ; Proteomics ; Mice ; Apoptosis/drug effects* ; Cell Line, Tumor ; Cell Proliferation/drug effects* ; Forkhead Box Protein O3/genetics* ; Xenograft Model Antitumor Assays ; Mice, Nude ; Mice, Inbred BALB C

Sini Decoction (SNT) is a traditional formula recognized for its efficacy in warming the spleen and stomach and dispersing cold. However, elucidating the mechanism of action of SNT remains challenging due to its complex multiple components. This study utilized a synergistic approach combining two-dimensional fluorescence difference in gel electrophoresis (2D-DIGE)-based drug affinity responsive target stability (DARTS) with label-free quantitative proteomics techniques to identify the direct and indirect protein targets of SNT in myocardial infarction. The analysis identified 590 proteins, with 30 proteins showing significant upregulation and 51 proteins showing downregulation when comparing the SNT group with the model group. Through the integration of 2D-DIGE DARTS with proteomics data and pharmacological assessments, the findings indicate that protein disulfide-isomerase A3 (PDIA3) may serve as a potential protein target through which SNT provides protective effects on myocardial cells during myocardial infarction.
Myocardial Infarction/genetics* ; Proteomics/methods* ; Drugs, Chinese Herbal/chemistry* ; Animals ; Protein Disulfide-Isomerases/genetics* ; Male ; Two-Dimensional Difference Gel Electrophoresis/methods* ; Humans ; Rats ; Rats, Sprague-Dawley ; Electrophoresis, Gel, Two-Dimensional

Biomanufacturing has emerged as a crucial driving force for efficient material conversion through engineered cells or cell-free systems. However, the intrinsic spatiotemporal heterogeneity, complexity, and dynamic characteristics of these processes pose significant challenges to systematic understanding, optimization, and regulation. This review summarizes essential methodologies for multi-omics data acquisition and analyses for bioprocesses and outlines modelling approaches based on multi-omics data. Furthermore, we explore practical applications of multi-omics and modelling in fine-tuning process parameters, improving fermentation control, elucidating stress response mechanisms, optimizing nutrient supplementation, and enabling real-time monitoring and adaptive adjustment. The substantial potential offered by integrating multi-omics with computational modelling for precision bioprocessing is also discussed. Finally, we identify current challenges in bioprocess optimization and propose the possible solutions, the implementation of which will significantly deepen understanding and enhance control of complex bioprocesses, ultimately driving the rapid advancement of biomanufacturing.
Fermentation ; Genomics/methods* ; Biotechnology/methods* ; Proteomics/methods* ; Models, Biological ; Metabolomics/methods* ; Bioreactors ; Multiomics

Adolescents and young adults (AYAs) are one of the major populations susceptible to tuberculosis. However, little is known about the unique characteristics and diagnostic biomarkers of tuberculosis in this population. In this study, 81 AYAs were recruited, and the high-quality serum proteome of the AYAs with tuberculosis was profiled by quantitative proteomics. The data of serum proteomics indicated that the relative abundance of hemoglobin and apolipoprotein was significantly reduced in the patients with active tuberculosis (ATB). The pathway enrichment analysis showed that the downregulated proteins in the ATB group were mainly involved in the antioxidant and cell detoxification pathways, indicating extensive oxidative stress damage. Random forest (RF) and extreme gradient boosting (XGBoost) were employed to evaluate protein importance, which yielded a set of candidate proteins that can distinguish between ATB and non-ATB. The analysis with the support vector machine algorithm (recursive feature elimination) suggested that the combination of apolipoprotein A-I (APOA1), hemoglobin subunit beta (HBB), and hemoglobin subunit alpha-1 (HBA1) had the highest accuracy and sensitivity in diagnosing ATB. Meanwhile, the levels of hemoglobin (HGB) and albumin (ALB) can be used as blood biochemical indicators to evaluate changes in the protein levels of APOA1 and HBB. This study established the serum proteome landscape of AYAs with tuberculosis and identified new biomarkers for the diagnosis of tuberculosis in this population.
Humans ; Proteomics/methods* ; Biomarkers/blood* ; Adolescent ; Young Adult ; Apolipoprotein A-I/blood* ; Machine Learning ; Tuberculosis/blood* ; Proteome/analysis* ; Male ; Hemoglobins/analysis* ; Female ; Blood Proteins/analysis* ; Adult

Phages, as obligate bacterial and archaeal parasites, constitute a virus group of paramount ecological significance due to their exceptional abundance and genetic diversity. These biological entities serve as critical regulators in Earth's ecosystems, driving biogeochemical cycles, energy fluxes, and ecosystem services across terrestrial and marine environments. Within soil microbiomes, phages function as microbial "dark matter," maintaining the soil-plant system balance through precise modulation of the microbial community structure and functional dynamics. Despite the growing research interests in soil phages in recent years, the proportion of such studies in environmental virology remains disproportionately low, which is primarily attributed to researchers' limited familiarity with the research methodologies for phage microecology, incomplete technical frameworks, and inherent challenges posed by soil environmental complexity. To address these challenges, this review synthesizes cutting-edge methodologies for soil phage investigation from four aspects: (1) tangential flow filtration (TFF)-based phage enrichment strategies; (2) integrated quantification approaches combining double-layer agar plating, epifluorescence microscopy, and flow cytometry; (3) multi-omics analytical pipelines leveraging metagenomics and viromics datasets; and (4) computational frameworks merging machine learning algorithms with eco-evolutionary theory for deciphering phage-host interaction networks. Through comparative analysis of methodological principles, technical merits, and application scopes, we establish a comprehensive workflow for soil phage research. Future research in this field should prioritize: (1) construction of soil phage resource libraries, (2) exploration of RNA phages based on transcriptomes, (3) functional characterization of unknown genes, and (4) deep integration and interaction validation of multi-omics data. This systematic methodological synthesis provides critical technical references for addressing fundamental challenges in characterizing soil phages regarding the community structure, functional potential, and interaction mechanisms with hosts.
Bacteriophages/physiology* ; Soil Microbiology ; Ecosystem ; Microbiota ; Metagenomics/methods*